检索结果-内蒙古大学图书馆

Combination of Fuzzy-Weighted Zero-Inconsistency and Fuzzy Decision by Opinion Score Methods in Pythagorean m -Polar Fuzzy Environment: A Case Study of Sign Language Recognition Systems

引用

International Journal of Information Technology and Decision Making 2023年第4期22卷 1341-1369页

作者： Albahri, O.S. Alsattar, H.A. Garfan, Salem Qahtan, Sarah Zaidan, A.A. Ahmaro, Ibraheem Y. Y. Alamoodi, A.H. Zaidan, B.B. Albahri, A.S. Al-Samarraay, Mohammed S. Jasim, Ali Najm Baqer, M.J. Department of Computing Faculty of Arts Computing and Creative Industry Universiti Pendidikan Sultan Idris Tanjung Malim 35900 Malaysia Department of Computer Center Middle Technical University's Baghdad Iraq Faculty of Engineering & It British University in Dubia Dubai United Arab Emirates Computer Science Department College of Information Technology Hebron University Hebron Palestine Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Baghdad Iraq Department of Business Administration College of Administrative Science The University of Mashreq Baghdad10021 Iraq

In the fuzzy multicriteria decision-making approach, a committee of decision-makers is usually involved in the assessment of the suitability of different alternatives based on the evaluation criteria by using linguistic terms and their equivalent fuzzy numbers. In this context, researchers have developed the Pythagorean fuzzy set (PFS) to overcome the limitation of intuitionistic fuzzy set in the description of decision-maker information such as imposing restrictions on the representation of membership and nonmembership grades. On the one hand, PFS still does not have sufficient ability and flexibility to deal with such issues. On the other hand, multipolar technology is used to operate large-scale systems in real-life situations, especially in dealing with dissatisfaction and indeterminacy grades for the alternatives of the reference set. Thus, m-polar fuzzy set is utilized and applied with other fuzzy sets because of its remarkable ability as a tool for depicting fuzziness and uncertainty under multipolar information in many circumstances. With the practical features of m-polar fuzzy set in combination with PFS, this paper employs it to extend two considerable MCDM methods, namely, fuzzy decision by opinion score method and fuzzy-weighted zero inconsistency. Such extensions, called Pythagorean m-polar fuzzy-weighted zero-inconsistency (Pm-PFWZIC) method and Pythagorean m-polar fuzzy decision by opinion score method (Pm-PFDOSM), are formulated to weight the evaluation criteria followed by alternative ranking progressively. The research methodology is presented as follows. Firstly, the mechanisms of Pm-PFWZIC and Pm-PFDOSM are formulated and integrated into the development phase. Secondly, the description of the real-world case study of the evaluation and benchmarking of the sign language recognition systems is adapted and presented. The result of Pm-PFWZIC shows that the criterion of 'finger movements' has the highest weight amongst the rest of the criteria, wherea

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Dynamic Network Slicing Control Framework in AI-Native Hierarchical Open-RAN Architecture

Dynamic Network Slicing Control Framework in AI-Native Hiera...

引用

International Conference on Information Networking

作者： Jongwon Han Minhyun Kim Jung Mo Moon Jeongho Kwak Department of Electrical Engineering and Computer Science DGIST Daegu South Korea ETRI Intelligent Small Cell Research Section Daejeon South Korea

ISBN: (数字)9798350330946

ISBN: (纸本)9798350330953

Network slicing is a promising technology in next-generation wireless networks that enables the division of a physical network infrastructure into multiple virtual networks, each of which is tailored for specific service requirements. This approach enables a more flexible allocation of network resources such as beamforming vector, bandwidth and transmit power; thereby effectively supporting services that require high data transmission rates. However, in dynamic network environments where multiple users dynamically move around; hence the interference relationships are dynamically varying, traditional static network slicing solution has critical drawbacks. To this end, for the effective implementation and performance improvement in practical and dynamic network environments, we first propose a dynamic network slicing control framework in AI-native hierarchical Open-RAN (Radio Access Network) architecture where mobility prediction and network controls are designed by multiple timescale decomposition. The proposed framework can facilitate effective network controls, enabling the generation of finely tuned QoS management decisions (power/ bandwidth allocation, user scheduling, beam activation) in different timescales. On top of this framework, we compare the performance of a simple dynamic network slicing algorithm and an existing static network slicing scheme via simulations.

关键词： Array signal processing Network slicing Heuristic algorithms Wireless networks Quality of service Vectors Resource management

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Recruitment Management: Optimizing Advanced Digital Solutions for Manpower Planning in Higher Education

Revolutionizing Recruitment Management: Optimizing Advanced ...

引用

IEEE Conference on Systems, Process & Control (ICSPC)

作者： Ahmad Mukafi Andrian Nor Kamaliah Khamis Ahgalya Subbiah Halimatuz Zuhriyah Safira Faizah Faculty of Information Sciences and Engineering Management and Science University Section 13 Shah Alam Selangor Department Informatics Engineering Faculty Engineering and Computer Science Jakarta Global University Depok Indonesia

ISBN: (数字)9798350391398

ISBN: (纸本)9798350391404

Effective manpower planning is crucial for any organization, including universities, as it directly influences performance, productivity, and overall success. Inefficient recruitment processes can lead to increased costs, higher turnover rates, and suboptimal utilization of human resources, negatively impacting the institution's ability to achieve its goals and maintain a competitive advantage. The objective of this study is to develop a comprehensive digital solution to streamline and enhance recruitment and manpower planning processes, replacing traditional manual methods. This paper presents the Recruitment and Manpower Planning System, an innovative web-based platform designed using Extreme Programming (XP) methodologies. The system integrates modern programming tools such as Visual Studio Code, Laragon, Laravel 9, and MySQL, and utilizes Unified Modelling Language (UML) for precise system design. A mixed-methods approach, incorporating quantitative data from structured questionnaires administered to 500 users, informed the system's design. Data analysis indicates a 40% reduction in recruitment time, a 35% increase in successful job placements, and a 90% user satisfaction rate. Rigorous testing phases ensured system accuracy and quality. This digital solution not only optimizes recruitment processes but also provides a robust prototype for future advancements in manpower planning systems.

关键词： Productivity Visualization Unified modeling language Prototypes Organizations Labor resources System analysis and design Programming profession Recruitment Testing

来源：评论

学校读者我要写书评

暂无评论

Teaching in student-centred active learning spaces: How relational, pedagogical, spatial, and technological aspects intertwine and affect the learning environment 51

Teaching in student-centred active learning spaces: How rela...

引用

51st Annual Conference of the European Society for engineering Education, SEFI 2023

作者： Korpås, G.S. Andersen, T.H. Kahrs, M.S. Hansen, G. Røren, K.A.F. Department of Physics Norwegian University of Science and Technology Trondheim Norway Department of Computer Science Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway Section for Teaching and Learning Support Education Quality Division Norwegian University of Science and Technology Trondheim Norway

来源：评论

学校读者我要写书评

暂无评论

EAMultiRes-DSPP: an efficient attention-based multi-residual network with dilated spatial pyramid pooling for identifying plant disease

引用

Neural Computing and Applications 2024年第26期36卷 16141-16161页

作者： Al-Gaashani, Mehdhar S. A. M. Muthanna, Ammar Chelloug, Samia Allaoua Kumar, Neeraj School of Resources and Environment University of Electronic Science and Technology of China 4 1st Ring Rd East 2 Section Sichuan Chengdu610056 China 6 Miklukho-Maklaya St Moscow117198 Russia Department of Telecommunication Networks and Data Transmission The Bonch-Bruevich Saint-Petersburg State University of Telecommunications 6 Miklukho-Maklaya St Saint Petersburg Saint Petersburg193232 Russia Department of Information Technology College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh610101 Saudi Arabia Department of Computer Science Thapar Institute of Engineering and Technology Patiala147004 India

Convolutional neural networks (CNNs) have made substantial contributions to the domain of plant disease diagnosis, attaining noteworthy levels of accuracy. The primary objective of this study is to enhance the capabilities of CNNs within this particular field. In this article, we suggest a unique strategy utilizing MultiRes blocks and attention mechanisms to enhance the classification performance of CNNs for plant diseases. Our solution involves stacking four MultiRes blocks, each of which gradually increases the number of filters to prevent excessive propagation of memory requirements to deeper network nodes. In order to collect more spatial information, we also implement a residual link and a 1 × 1 convolutional layer. After each MultiRes block, we employ a Convolutional Block Attention Module to emphasize vital information and decrease redundant noise by inferring attention mappings along the channel and spatial dimensions. Finally, our method includes the use of a Dilated Spatial Pyramid Pooling module which is designed to extract information from the input image at various scales. Our evaluation leveraged a comprehensive dataset compiled from multiple sources, including the New Plant Diseases Dataset, Corn Dataset, and Coffee Dataset, encompassing a wide range of plant leaves both healthy and diseased, across various classes. This diverse collection of images, augmented by several techniques to enhance data variance and model robustness, provided a solid foundation for assessing the performance of our proposed model. Experiments demonstrate that this method outperforms conventional machine learning techniques and delivers high classification accuracy for plant diseases, with a precision of 99.34%, recall of 99.25%, f1-score of 99.29%, and accuracy of 99.35%. Our proposed model has the potential to considerably enhance the effectiveness and efficiency of diagnosing plant diseases in the agricultural industry. © The Author(s), under exclusive licence to Springer-

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Eight-direction least-square phase unwrapping algorithm for optical three-dimensional measurement 3

Eight-direction least-square phase unwrapping algorithm for ...

引用

3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： He, Yantao Liu, Sijia Pan, Minling Wang, Rongfu Li, Xueri Zhang, Rong Department of Computer Science Guangdong University of Science and Technology No. 2 Songshan Lake Section 523668 China School of Mechanical Engineering Hunan University of Science and Technology Taoyuan Road 411201 China School of Electronics and Information Engineering Beibu Gulf University No. 12 Binhai Avenue 535011 China

ISBN: (纸本)9781510668522

The least-square method is widely used in the fast phase unwrapping of optical three-dimensional measurement due to its high-speed and comprehensive characteristics. In order to solve the problem of measurement error propagation in the phase unwrapping algorithm based on least-square method, an improved eight-direction least-square phase unwrapping algorithm is proposed in this paper. This algorithm not only researches the gradient difference between the target phase and its eight-neighbor phases, improving measurement accuracy and reducing measurement errors. The superiority and robustness of this algorithm have been demonstrated through simulation data and measurement of industrial bearing roller end faces © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Measurement errors

来源：评论

学校读者我要写书评

暂无评论

Belief-Rewards to Learn Radar Scheduling Policies

Belief-Rewards to Learn Radar Scheduling Policies

引用

IEEE National Conference on Radar

作者： Amos Hebb Raviraj S. Adve Zhen Qu Zhen Ding Department of Electrical and Computer Engineering University of Toronto Toronto Canada Radar Sensing and Exploitation Section Defence Research and Development Canada (DRDC) Ottawa Canada

ISBN: (数字)9798350329209

ISBN: (纸本)9798350329216

Beam-agile radars have the potential to learn scheduling policies requiring only a holistic belief constructed from past observations. Rewarding improvements to belief directly enables an agent to learn policies to track known targets and search for unknown targets, without explicitly rewarding this behavior. In this paper, we model a radar controller as an information-gathering agent in a Belief Markov Decision Process. Using a Reinforcement Learning solver to develop a Monte Carlo Tree Search policy, actions are chosen considering only belief and a model estimating the improvement in belief-reality distance. Importantly, our approach is agnostic to the number of targets and adapts to dynamic environments. We present preliminary results as proof of our underlying concept.

关键词： Training Adaptation models Target tracking Monte Carlo methods Markov decision processes Neural networks Radar

来源：评论

学校读者我要写书评

暂无评论

Improving Clinical Decision-Making with Polynomial Regression-Based Real Patient State Estimation

Improving Clinical Decision-Making with Polynomial Regressio...

引用

2023 International Automatic Control Conference, CACS 2023

作者： Hung, Chia-You Newton Fernando, Owen Noel Wang, Chung-Yih Chen, Kuo-Wei Samani, Hooman Yang, Chan-Yun National Taipei University Department of Electrical Engineering Taipei City Taiwan Nanyang Technnological University School of Computer Science and Engineering Singapore Cheng Hsin General Hospital Department of Radiation Oncology Taipei City Taiwan Cheng Hsin General Hospital Section of Hematology and Oncology Department of Internal Medicine Taipei City Taiwan Creative Computing Institute University of the Arts London London United Kingdom National Taipei University Department of Electrical Engineering New Taipei City Taiwan

ISBN: (纸本)9798350306354

As science and technology continue to evolve, clinical decision-making has become increasingly important in the field of medicine. This process not only aids experienced clinicians in making critical decisions but also provides guidance for those who lack experience. However, in the past, clinicians had to rely solely on their own expertise and medical reports to analyze patients, resulting in a time-consuming process. To address this issue, a scoring model was developed that analyzes patient conditions based on each parameter's value using data collected by the hospital. By utilizing computer analysis, evaluations, predictions, and optimizations, a suitable model for clinicians and patients can be created. This paper proposes a nonlinear polynomial regression approach as a model for predicting patient health scores, which has been validated through computer simulations and fits multiple researches and clinical examinations. The predicted results have been consistent with actual results when using the model, making it easier for clinicians to make clinical decisions. In summary, this model not only analyzes patient conditions but also predicts patient health scores with the support of appropriate parameters, making it a valuable tool for clinicians in their clinical decision-making process in the near future. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Phase Optimization and Relay Selection for Joint Relay and IRS-Assisted Communication 100

Phase Optimization and Relay Selection for Joint Relay and I...

引用

100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Uyoata, Uyoata E. Akinsolu, Mobayode Obayiuwana, Enoruwa Sangodoyin, Abimbola Adeogun, Ramoni Aalborg University Wireless Communication Network Section Aalborg Denmark Wrexham University Faculty of Arts Computing and Engineering WrexhamLL11 2AW United Kingdom Obafemi Awolowo University Department of Electronic and Electrical Engineering Ife Nigeria University of Lincoln School of Computer Science LincolnLN6 7TS United Kingdom

ISBN: (纸本)9798331517786

The use of Intelligent Reflecting Surfaces (IRSs) is considered a potential enabling technology for enhancing the spectral and energy efficiency of beyond 5G communication systems. In this paper, a joint relay and intelligent reflecting surface (IRS)-assisted communication is considered to investigate the gains of optimizing both the phase angles and selection of relays. The combination of successive refinement and reinforcement learning is proposed. Successive refinement algorithm is used for phase optimization and reinforcement learning is used for relay selection. Experimental results indicate that the proposed approach offers improved achievable rate performance and scales better with number of relays compared to considered benchmark approaches. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence Scoring Algorithm for English Translation Based on DNN 2

Artificial Intelligence Scoring Algorithm for English Transl...

引用

2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Priya, R. Krishna Aanandha Saravanan, K. Gadgil, Aashish A. Sabarmathi, K.R. Niranjanamurthy, M. Azarudeen, K. Department of Engineering-Electrical section College of Engineering and Technology University of Technology and Applied Sciences Shinas Oman Department of ECE Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and technology Chennai India Department of ECE KLS GOGTE institute of Technology Karnataka Belagavi India Department of Information Technology Bannari Amman Institute of Technology Tamilnadu Sathyamangalam India Department of AI and ML BMS Institute of Technology and Management Avalahalli. Karnataka Bangalore India Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (纸本)9798350305418

With the popularity of languages and the increasing demand for language translation, the optimization of artificial intelligence scoring algorithm for English translation has become the urgent need of the translation market. Based on the deep neural network(DNN) algorithm, it continuously integrates modern technology to realize information collection, storage, analysis and application, which promotes the deep integration of the DNN algorithm in the field of intelligent identification and expands the application scope of artificial intelligence identification technology. This paper focuses on how to efficiently optimize the model of English translation artificial intelligence scoring algorithm by DNN, specifically studying the DNN model, by studying the mathematical model and algorithm flow of the DNN optimization algorithm, and the basic principle of the DNN model;Based on the DNN model, a learning ability analysis model of English translation algorithm is proposed. Experiments show that this model can optimize the artificial intelligence scoring algorithm of English translation. © 2023 IEEE.

关键词： Artificial intelligence scoring algorithm DNN English translation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：